Archaeal and Bacterial Communities in Acid Mine Drainage from Metal-Rich Abandoned Tailing Ponds, Tongling, China

Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342

Archaeal and bacterial communities in acid mine drainage from metal-rich abandoned tailing ponds, Tongling, China

Yang YANG, Yang LI, Qing-ye SUN

School of Resources and Environmental Engineering, Anhui University, Hefei 230601, China

Received 5 September 2013; accepted 27 February 2014

Abstract: To expand knowledge on microbial communities of various metal-rich levels of mine drainage environments in Anhui province, China, the archaeal and bacterial diversities were examined using a PCR-based cloning approach. Eight acid mine water samples were collected from five areas in Tongling. Phylogenetic analyses revealed that bacteria mainly fell into ten divisions, which were Betaproteobacteria, Gammaproteobacteria, Alphaproteobacteria, Deinococcus-Thermus, Nitrospira, Firmicutes, Actinobacteria, Deltaproteobacteria, Bacteroidetes, Chloroflexi. Archaea fell into three phylogenetic divisions, Thermoplasma, Ferroplasma and Thermogymnomonas. The unweighted pair group method with arithmetic mean (UPGMA) cluster analysis based on the microbial communities’ compositions revealed that five samples shared similarity with the dominance of Meiothermus and Thermomonas. Two samples had the preponderant existence of Acidithiobacillus and Leptospirillum. The remaining sample owned higher microbial communities’ diversity with the Shannon-Weaver H up to 2.91. Canonical correlation analysis (CCA) suggested that 2+ 2+ 3+ − 2− microbial community structures had great association with pH and the concentration of Hg , Pb , Fe , Cl , SO4 in water. Key words: acid mine drainage; microbial community; clone library; geochemical variables

host rock [3]. 1 Introduction Despite the acidic nature and elevated dissolved metal concentrations, the water still has the presence of Acid mine drainage (AMD) water is a worldwide microorganisms. Previous studies based on the diversity environmental problem caused by active and abandoned of microorganisms in AMD with extremely low pH (<2) mines [1]. It has caused severe environmental problems, showed that acidophilic bacteria mainly included a group including contamination of rivers, streams and ground of sulfur and/or iron-oxidizers, classifying into water. AMD arises when metal sulfide minerals, Acidithiobacillus ferrooxidans, Acidithiobacillus particularly pyrite (FeS2), are exposed to oxygen and thiooxidans, Leptospirillum ferrooxidans and water during the mining of metals and coals [2]. The Ferroplasma spp. [4,5]. With the application of overall procedure can be described as follows: FeS2+ unculture-based molecular phylogenetic techniques, the 3+ 2+ 2− + 14Fe +8H2O→15FeS +2SO4 +16 H [3], and the understanding of the diversity of acidophilic ongoing oxidation of sulfide minerals really depends on microorganisms was accelerated, including Legionella, the regeneration of ferric iron. At pH values below 4, the Thiomanas and Gallionella [6]. rate of chemical oxidation of ferrous iron by O2 is The distribution of acidophiles in AMD has close negligible [4]; therefore, the activities of acidophilic association with temperature, pH and metal iron-oxidizing microorganisms play a pivotal role in concentrations [3]. In general, mesophilic acidophiles converting ferrous to ferric iron in acidic environment can be exclusively detected in AMD, though increased [1]. Due to the low pH of AMD, the solubility of temperature makes the moderate thermophiles dominate transition metals is greater and so AMD often typically in the microbial populations, such as Bacillus spp. and contains elevated concentrations of metals, including Sulfobacillus acidophilus [7]. Conversely, in many low- iron, aluminium, manganese and other toxic transition temperature AMD waters, Acidithiobacillus ferrivorans, metals who present depending on the mineralogy of the the newly described psychrotolerant species, tend to

Foundation item: Project (41171418) supported by the National Natural Science Foundation of China Corresponding author: Qing-ye SUN; Tel: +86-13866755085; Fax: +86-551-63861882; E-mail: [email protected] DOI: 10.1016/S1003-6326(14)63474-9

Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342 3333 dominate over A. ferrooxidans and L. ferrooxidans. amount of chalcopyrite. Tongguanshan tailing pond was Another controlling factor of microbial populations is discarded in 1991, from which samples B and C were pH. A. ferrooxidans and L. ferrooxidans, as the typical collected. Samples D and G were collected from iron-/sulfur-oxidizing microbes, dominate in extreme Shuimuchong tailing pond and Chaoshan gold mine, acidic environment (pH<2); the moderate acidophiles, respectively. There were four samples collected from such as Thiomonas and Halothiobacillus, dominate in Yangshanchong tailing pond, named E, F, H and I. This moderately acidic AMD (pH 3−6) [1,8]. The low pH of tailing pond began natural ecological restoration process AMD results in the solution of metals. The composition after being discontinued in 1991. Tailing wasteland is of AMD is also influenced by the concentrations of mainly composed of stone powder and sandy texture, and metals [3], such as Fe, Cu, and As. Besides, the low the main mineral in tailings is calcium iron (aluminum) concentration of arsenic might facilitate a higher garnet, quartz, feldspar and pyroxene. Sample J was community proportion of Acidithiobacillus [9]. The collected from Heishahe tailing pond, which has been composition of various tailing ponds may influence the discharged for more than 50 years. Due to the fluctuation dissolved elements in AMD. Previous studies showed of the Yangtze River, many naturally colonized plants that the microbial communities differed with the various grew here; moreover, oilseed rape and some other crops tailing ponds. HAO et al [6] detected the dominance of were planted by the local farmers, so tailing substrate chemoorganotrophic and photosynthetic metabolisms, was greatly improved [11]. such as Acidiphilium, based on the research of sulfide mine in Xiang Mountain, Anhui province. XIAO et al 2.2 Samples collection [10] showed that samples collected from Yunfu sulfide A total of ten AMD samples were collected from mine were rich in Acidithiobacillus, while waters from five different tailing ponds in Tongling, Anhui Province, Yinshan lead−zinc mine were dominanted in China, on February, 2012. The pH values of samples B Leptospirillum; in addition, there was no detection of (7.83) and J (6.08) went over 6.0, so they did not belong archaea in the study [10]. to the acidic waste water. They were excluded from the Although there have been some reports on the samples. For the eight remaining samples, approximately bacterial ecology of AMD, few detailed studies were on 10 L of water was collected from these tailing ponds, and the various acidification levels of AMD involving then transported to the laboratory within 24 h. About 500 different abandoned tailing ponds. The major objectives mL original water of each sample was taken out for of this study were: to investigate the archaeal and geochemical analysis, and the remaining water of each bacterial communities of mine drainage from different sample was filtered through 0.22 µm hyper filtration mineral compositions of five main tailing ponds using a membrane with vacuum pump, respectively. These filters PCR-based cloning approach, and to explore the were then immediately transferred to a tube and stored at geochemical factors, resulting in community changes of −20 °C until they were used for analysis. The filtered mine drainage in tailing ponds. water samples were for chemical analysis.

2 Experimental 2.3 Geochemical analysis of water samples Latitude and longitude of sampling sites were 2.1 Sites description determined using a hand holding GPS. The 2− − Tongling, located in the southern bank of the middle measurements of SO4 , Cl and PO4−P were carried by and lower reaches of Yangtze River, has the subtropical ion chromatography (ICS−1500), NH4−N and NO3−N by monsoon climate, with an annual average temperature of UV spectrophotometry. 16.2 °C and the summer average temperature of 27.4 °C. Elemental analysis was carried out using On average, the frost-free period is 237−258 d, and inductively coupled plasma-atomic emission rainfall is abundant with the mean annual precipitation of spectrometry (ICP-AES) (XSP Intrepid II, USA). Each 1390 mm and mean annual humidity of 75%−81% sample was tested in the presence of 20 elements, Al, As, [11,12]. Ba, Be, Ca, Cd, Co, Cu, Fe, Hg, K, Li, Mg, Mn, Na, Ni, Among these six study areas, there were five tailing Pb, Se, Ti and Zn. ponds, Jinkouling, Tongguanshan, Shuimuchong Yangshanchong and Heishahe, discarded from 1980s to 2.4 DNA extraction and purification 2010s; the rest one was still under use, named Chaoshan Each millipore filter was cut and placed into a 1.5 gold mine [13]. Sample A was collected from Jinkouling mL falcon tube, and then nucleic acids extraction was tailing pond, which had been discarded for 20 years; and carried out according to the established procedures [13]. the bed rock was composed of pyrrhotite, pyrite, The crude DNA was purified by agarose gel magnetite, hematite, limonite, siderite and a small electrophoresis (1%) and the Wizard DNA Clean-Up Kit

3334 Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342

(Promega, Madison, Wis.). DNA was quantified by formula: H=−∑(pi)(lnpi), where pi is the relative UV-visible spectrophotometry (Thermo, USA). abundance of the clone sequenced in each sample. Unweighted pair-group method with arithmetic means 2.5 PCR and amplification of 16S rDNA (UPGMA) was performed to reveal the distance In the reactions, bacterial 16S rDNA genes relationship between sample by the archaeal and were amplified with the primer set 27F bacterial communities. Statistical product and service (5’-AGAGTTTGATCCTGGCTCAG-3’) and 1492R solution (SPSS) were conducted to reveal the correlation (5’-CGGCTACCTTGTTACGACTT-3’). A PCR between geochemical variable and community structure. amplifier (Biometra, T-Grandient, Germany) was used to incubate reactions through an initial denaturation at 2.9 Nucleotide sequence accession number 94 °C for 2 min, followed by 35 cycles at 94 °C for 40 s, Sequences have been submitted to GenBank with 55 °C for 30 s, and 72 °C for 1 min, and completed with accession numbers as follows: KC537424-KC537737, an extension period of 10 min at 72°C. Products from the KC620584-KC620676, KC620745- KC620899 and amplification reactions of expected size (about 1500 bp) KC749063-KC749417. were pooled and purified before ligation later. PCR amplification of archaeal 16S rDNA genes was 3 Results carried out following the PCR reactions described as above with archaea-specific primer set: 3.1 Physico-chemical characteristics of samples Arch-21F(5’-TTCYGGTTGATCCYGCC RGA-3’) and The samples were all collected from the exposed pit Arch-958R (5’-YCCGGCGTTGAMTCCAWTT-3’) to outdoor, and the temperatures of them were all about 10 yield 900 bp PCR products. °C. The pH values of the eight sites were not

substantially different from each other in the range of 2.6 Cloning and sequencing 2−4. The pH values of samples A, D, G, I were under 2.5, The purified PCR products were ligated to the and the colors of these samples were dark red, especially pEASY-T3 cloning vector using a rapid ligation kit for sample D, with the strongest acidity (pH=2.04) and according to the instructions of the manufacturer the deepest color (brown). The samples all contained (Transgen, Beijing, China), and then transformed to high levels of SO 2−, Ca2+, Fe3+ and Mg2+; and the competent Escherichia coli cells (Transgen, Beijing, 4 concentration of Ca2+ was even higher than that of Fe3+, China). The transformed cells were plated onto maybe resulting from the surrounding tailings(Table 1). Luria-Bertani agar plates in the presence of ampicillin. Besides, sample D had the highest concentrations of After about 14 h of incubating at 37 °C, about 150 white SO 2−, nitrate and electrical conductivity (EC). The ionic colonies were randomly selected from each library, 4 contents of samples A, G and I were also generally followed by the sequencing of single clone (BGI, Beijing, higher than other samples, and the ion concentrations PRC). varied widely. As shown in Table 1, sample C had the 2.7 Phylogenetic analysis highest concentration of Mg, while sample E had the 3− The nucleotide sequences were manually checked highest NH4−N, sample F had the highest PO4 −P. for chimeras using Ribosomal Database Project II. Meanwhile, other ion concentrations also fell in a wide Identified chimeric sequences were discarded. range. As to the rest ions, Co, Cd, Ba, Li, Hg levels were Operational taxonomic units (OTUs) were determined by ignorable. neighbor-joining analysis of Mega 4.0, which shows the phylogenetic relationships of bacterial 16S rRNA gene 3.2 Analysis of 16S rDNA cloning libraries sequences recovered from these AMD samples. The The PCR products of 16S rDNA gene with the coverage of clone libraries was calculated using the expected size (bacteria 1500bp and archaea 900bp) were successfully amplified from community genome DNA of equation: Rcov=1−n/N, where n is the number of clones that occurred only once and N is the total number of the samples. After TA cloning, a total of 856 positive analyzed clones in each clone library [14]. colonies (603 for bacteria, 253 for archaea) were obtained from the eight AMD samples. 2.8 Statistical methods In order to test whether the analyzed clones could Canonical correspondence analysis (CCA) was represent the bacteria community in each sample, the performed to analyze the geochemical variables and coverages of all clone libraries were calculated (Table 2). community structure with CANOCO (Version 4.5, All samples had the coverage over 90%, which suggested Biometris-Plant Research International, Netherlands) that the obtained data could represent the real (Terbraak 1988). To evaluate the community diversity, communities of bacteria. Number of OTUs in each Shannon-Weaver index (H) was calculated using the sample is quite different from each other, with a range of

Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342 3335

Table 1 Physico-chemical characteristics of collected AMD samples − 3− 2− 2+ 3+ 2+ 3+ COD/ ρ(Cl )/ ρ(PO4 −P)/ ρ(SO4 )/ ρ(NH4−N)/ ρ(NO3−N)/ EC/ ρ(Ca )/ ρ(Fe )/ ρ(Mg )/ ρ(Al )/ Sample pH (mg·L−1) (mg·L−1) (mg·L−1) (g·L−1) (mg·L−1) (mg·L−1) (ms·cm−1) (mg·L−1) (mg·L−1) (mg·L−1) (mg·L−1) A 2.65 104.04 17.86 7.14 2.343 2.27 17.23 3.63 228.90 73.88 35.15 5.37 C 3.37 60.26 3.20 5.13 2.297 0.96 1.42 3.35 253.70 47.47 82.73 20.40 D 2.11 63.04 2.60 5.00 6.272 1.72 126.26 5.89 111.10 121.20 26.16 9.84 E 2.70 156.33 8.65 4.90 1.841 4.81 33.04 3.11 186.50 17.23 6.31 11.49 F 3.48 143.84 9.61 8.76 0.833 3.74 27.03 1.81 165.00 8.48 4.20 5.02 G 2.33 28.14 3.67 4.89 3.865 3.28 34.46 4.58 138.60 62.81 28.76 33.71 H 2.54 155.78 2.24 4.90 2.651 2.00 43.57 3.59 357.50 108.10 16.44 5.23 I 2.40 156.97 4.82 4.89 2.982 4.23 38.86 3.85 423.30 151.80 17.25 23.66

+ 2+ 2+ 2+ 2+ + 3+ 2+ 2+ 2+ + ρ(Na )/ ρ(Zn )/ ρ(Mn )/ ρ(Cu )/ ρ(Pb )/ ρ(K )/ ρ(As )/ ρ(Co )/ ρ(Cd )/ ρ(Ba )/ ρ(Li )/ ρ(Hg2+)/ Sample (mg·L−1) (mg·L−1) (mg·L−1) (mg·L−1) (mg·L−1) (mg·L−1) (mg·L−1) (μg·L−1) (μg·L−1) (μg·L−1) (μg·L−1) (μg·L−1) A 8.00 1.90 3.53 2.25 0.04 1.40 0.71 95.00 38.00 16.00 8.00 10.00 C 1.96 1.41 6.16 1.45 1.62 3.37 − 229.00 − 8.00 17.00 9.00 D 0.59 0.37 0.70 2.23 4.55 0.30 − 121.00 − 9.00 9.00 23.00 E 7.77 3.11 1.68 2.88 1.78 0.67 0.10 4.00 17.00 12.00 10.00 9.00 F 14.73 1.52 0.91 2.80 1.64 1.05 0.02 24.00 9.00 19.00 8.00 15.00 G 1.37 11.40 4.20 4.48 3.11 0.35 0.57 89.00 7.00 9.00 27.00 7.00 H 0.56 5.61 2.61 2.24 1.94 0.45 2.92 33.00 48.00 6.00 14.00 13.00 I 5.75 10.94 3.47 6.44 0.07 0.51 1.56 91.00 83.00 11.00 27.00 8.00

Table 2 Analyses of bacterial 16S rDNA clones libraries Table 3 Analyses of archaeal 16S rDNA clones libraries constructed for AMD from Tongling constructed for AMD from Tongling Number Coverage/ Shannon- Number Coverage/ Shannon- Sample OTUs Sample OTUs of clone % weaver index H of clone % weaver index H A 93 20 92.47 2.36 A 31 2 100.00 0.24 C 71 6 98.59 1.21 C 27 3 100.00 0.67 D 72 10 95.83 1.17 D 30 3 96.67 0.68 E 73 12 95.89 1.95 E 32 4 100.00 1.16 F 72 6 97.22 1.07 F 31 4 100.00 1.22 G 68 10 91.18 1.49 G 35 3 100.00 1.12 H 71 5 98.59 1.16 H 35 3 100.00 0.57 I 83 12 93.98 1.39 I 32 4 93.75 0.89

5−20. Sample A had the most OTUs (27), sample E (12) 3.3 Phylogenetic analysis of bacterial sequences and sample I (12) the second, sample C (6), sample F (6) Phylogenetic analysis was established by a next, sample H (5) was the lowest. This suggested that bootstrap neighbor-joining method, and the 16S rRNA there contained less kinds of bacteria in samples C, F and gene sequences of the bacterial library fell into ten H. phylogenetic divisions: Betaproteobacteria, There were at least 27 archaeal cloning sequences Gammaproteobacteria, Alphaproteobacteria, obtained for each sample, but only four patterns of OTUs Deinococcus-Thermus, Nitrospira, Firmicutes, were found, and not all samples contained the four OTUs Actinobacteria, Deltaproteobacteria, Bacteroidetes, (Table 3). From the coverage, it could be shown that the Chloroflexi and some unknown bacterial clusters number of clones tested in the experiment was sufficient (Table 4). to detect the level of archaeal community diversity The Gammaproteobacteria group was ubiquitous in within these eight samples. these eight samples. For samples A, D, I, the group

3336 Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342

Table 4 Relative abundance of bacterial clones affiliated with each major group Relative abundance/% Samlple Betaproteobacteria Gammaproteobacteria Alphaproteobacteria Deinococcus-Thermus Nitrospira A 54.84 29.03 1.08 − 5.38 C 4.23 45.07 11.27 39.44 − D − 72.22 9.72 − 9.72 E 4.11 46.58 9.59 27.40 5.48 F 2.78 40.28 9.72 47.22 − G 1.47 39.71 20.59 36.76 − H 1.41 45.07 14.08 39.44 − I 6.02 45.78 − − 42.17 Relative abundance/% Sample Firmicutes Actinobacteria Deltaproteobacteria Bacteroidetes Chloroflexi Others A − 3.23 − 6.45 − − C − − − − − − D 4.17 2.78 − − 1.39 − E 1.37 − 5.48 − − − F − − − − − − G − − − − − 1.47 H − − − − − − I 2.41 − 3.61 − − − was mainly classified by Acidithiobacillus with the The phylogenetic diversity was evaluated for each proportion of 17.20% (A), 70.83% (D) and 40.96% (I) of sample from the clone data by Shannon-Weaver index H. total bacterial clones. Sample A still contained the genus The results showed that sample A (H=2.36) had the of Halothiobacillaceae and Legionella. For samples C, E, preeminent diversity, followed by sample E (H=1.95), F, G, H, Gammaproteobacteria was almost composed of while sample F (H=1.07) possessed the lowest H, which Thermomonas (45.07%, 31.51%, 40.28%, 35.29% and was less than half of sample A (Table 3). The remaining 43.66%). Betaproteobacteria was detected in samples five samples approximately shared almost the same but sample D, with the dominant in sample A. The group diversity, in the range of 1.16−1.49. was mainly constituted of Massilia, Herminiimonas (4.30% and 5.38%) in the family of Oxalobacteraceae; 3.4 Phylogenetic analysis of archaeal sequences Polaromonas (5.38%) in Comamonadaceae; Archaeal lineages reported from AMD Thiobacillus and Sulfuricella (8.60% and 20.43%) in environments were restricted to the Thermoplasmatales Hydrogenophilaceae for sample A. Alphaproteobacteria and Sulfolobales [15]. In our study, the archaeal clones widely distributed in the samples except sample I. For were tested and all belonged to Thermoplasmatales, with sample D, the group was almost composed of no appearance of Sulfolobales. Archaea detected in the Rhodobacter (5.56%), Phyllobacteriaceae. Samples C, E, ten samples fell into three known phylogenentic F, G and H had the proportions of 7.04%, 4.11%, 9.72%, divisions, Thermoplasma, Ferroplasma, 14.71%, 8.45%, respectively. Thermogymnomonas and a genus unclassified. The The genus of Meiothermus, in the family of difference between each other was the percentage of Deinococcus- Thermus, had the largest proportions in archaea communities. For samples E, F and G, samples C, E, F, G and H (39.44%, 27.40%, 47.22%, Thermoplasma (E:56.25%; F:51.61%; G:48.57%) 36.76% and 39.44%), but it is not detected in other occupied an important advantage over Ferroplasma samples. Leptospirillum in the family of Nitrospira (E:18.75%; F:16.13%; G:34.29%). For the rest five appeared in samples A, D, E and I, and gained samples A, C, D, H and I, Ferroplasma (A: 93.55%; C: superiority especially in sample I (42.17%). Firmicutes 77.78%; D: 73.33%; H: 82.86%; I: 59.38%) was several was detected in samples D, E and I with no significant times. Thermoplasma (A: 6.45%; C: 14.81%; D: 23.33%; advantage. Actinobacteria was found in samples A and D, H: 11.43%; I: 34.38%). Samples E, F, H and I had the remaining Deltaproteobacteria was detected in Thermogymnomonas with the relative abundance of samples E and I; Bacteroidetes, Chloroflexi only 12.50%, 19.35%, 5.71% and 3.13%, respectively appeared in samples A and D, respectively. (Table 5).

Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342 3337

Table 5 Relative abundance of archaeal clones affiliated with each major group Relative abundance/% Sample Ferroplasma Thermoplasma Thermogymnomonas Unclassified A 93.55 6.45 − − C 77.78 14.81 − 7.41 D 73.33 23.33 − 3.33 E 18.75 56.25 12.5 12.5 F 16.13 51.61 19.35 12.9 G 34.29 48.57 − 17.14 H 82.86 11.43 5.71 − I 59.38 34.38 3.13 3.13

The diversity index of archaea was generally low correspondence analysis (CCA) was performed with the for these eight samples, and the highest diversity index phylogenetic microbial communities of OTUs and each reached 1.22 only, which showed that the archaeal geochemical variable; at last, there were six significant communities of acidic waste water were quite limited. correlation geochemical variables (Fig. 2). The result Especially for sample A, there were only two OTUs showed that geochemical variables influenced detected, with the diversity index of 0.24, which was the distribution of samples, especially the pH and the 2+ 2+ − 3+ 2− 3+ lowest value in all. And the rest samples were almost contents of Hg , Pb , Cl , Fe and SO4 . Fe and pH limited (Table 3). made more contribution to the distribution of microorganisms. The distribution of samples D and I 3.5 Statistical analysis might have close association with the contents of Cl− and 3.5.1 UPGMA cluster analysis of clone libraries 2− SO4 . The complexity of the microbial communities of UPGMA cluster analysis based on the microbial samples C, F, G and H might be due to the effects of communities’ compositions including bacteria and many geochemical variables. archaea in the eight samples was used to reveal the microbial communities’ relationship among them. This suggested that samples C, E, F, G and H had more similarity in microbial community structure among the eight samples (Fig. 1). The percentage of similarity reached between 66.98% and 88.24% for the predominance of Thermomonas and Meiothermus. Besides, samples D and I had 62.67% similarity with the rich Acidithiobacillus and Leptospirillum. There was a varied quite different from others for the abundance of microbial communities’ diversity.

Fig. 2 CCA based on microbial communities’ compositions and some significant correlation geochemical variables

4 Discussion

AMD is an extremely acidic environment with low

Fig. 1 UPGMA cluster analysis based on microbial pH and high levels of metal concentrations [16]. The communities’ compositions of water samples investigation on this extreme environment can not only help us to understand the community structures of 3.5.2 Relations between phylogenetic microbial different acid mines relative to environment pollution, community and geochemical variables but also provide useful information about bioleaching. In To determine the key geochemical variables shaping this work, the bacterial community structures of these microbial community structure, canonical tailing ponds were identified. Moreover, multivariate

3338 Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342 analysis was performed to analyze the relationship Acidithiobacillus spp. is widely considered to be the between the geochemical variables and microbial microorganism that controls the generation rate of AMD communities. and Acidithiobacillus ferrooxidans has been used as The geochemical property of AMDs is model microbe in bioleaching system [19]. heterogeneous, and due to the low pH of AMD, the Acidithiobacillus thiooxidans which can oxidize only solubility of transition metals is great, containing sulfur and A. ferrooxidans which can oxidize sulfur and elevated concentrations of metals [3]. In these studied reduce inorganic sulfur compounds in addition to ferrous samples, the contents of S, Ca, Fe, Mg, Al, Na, Zn, Mn, iron[3], were both detected in our samples. The Cu elements were very high, which was consistent with proportion of Acidithiobacillus in each sample was the previous reports [17]. AMDs have different 17.20% for sample A, 70.83% for sample D, 10.96% for characters in geochemical backgrounds (i.e., element sample E and 40.96% for sample I. The largest composition in bedrock, and wall rock), which depend proportion of clones affiliated with Acidithiobacillus upon the location of the mining site, thus the element (70.83%) was detected in sample D, which showed that concentration of the AMDs varies in different locations this site might be the most suitable for the growth of the all over the world [8]. For these eight samples, the organisms among these samples. Previous researches content of S, Ca, Fe was much higher than others, reported that Acidithiobacillus spp. was very sensitive to especially for Ca element, which might result from the arsenic ions, especially arsenic ion (III) [18]. The composition of bedrock. In addition, AMD may also be concentration of element arsenic in sample D was not affected by other minerals, such as silicates, which will detected, and the pH was the lowest among all samples. lead to an increase in the dissolved extents of Na, K, Mg, Acidithiobacillus occupied a higher community Ca, Si, and Al [8]. In this study, the samples were proportion which might have been facilitated by the low obtained from five main areas with the pH 2.0−3.5 at the arsenic concentration and low pH. For sample I, the temperature around 10 °C, and the samples were percentage of Acidithiobacillus was the second, and the collected in the exposed pit outdoor. concentration of element arsenic was the highest among According to the UPGMA cluster analysis, the these five samples (1.56 mg/L). Compared with others, microbial communities’ compositions could be divided such as the arsenic concentration of 2.5−29 mg/L into three parts, including the samples rich in iron-/ reported by XIAO et al [10], the arsenic concentration sulfur-oxidizing microorganisms, such as samples D and might not reach the inhibition extent. From the result of I; the samples rich in moderate acidophiles (Meiothermus, SPSS, the dominance of Acidithiobacillus had significant 3+ − Thermomonas), such as samples C, E, F, G and H [18]; association with the concentrations of Fe , NO3 and 2− and sample A without dominant species but with SO4 and EC value. abundant diversity. Members of the genus Leptospirillum were also detected in the four samples, but the percentage was very 4.1 Communities of putative iron-/sulfur-oxidizing different, with the largest occupation in sample I bacterial in related samples (42.17%), and the rest was identically lower. It should be For these eight samples, four samples had the attributed to the concentration of iron element and pH existence of putative iron-/sulfur-oxidizing bacteria, and values of four samples. Previous studies with respect to the percentage of them in each sample is enumerated in Leptospirillum spp. suggest that these organisms could Table 6. The results showed that bacteria participated in only use reduced iron as energy resource and occupy a the process of iron-/sulfur-oxidizing fell into the greater percentage of the community structure at low pH following seven genera, with a significant advantage in [20]. The concentration of iron element was 73.9 mg/L samples D and I, with the proportion up to 86.11% and for sample A, 121.2 mg/L for sample D, 17.2 mg/L for 84.34% respectively. Members of the genus sample E, 151.8 mg/L for sample I, and the pH values Acidithiobacillus and Leptospirillum were ubiquitous in were 2.6, 2.04, 2.67, 2.4, respectively. Sample D had the the following four samples, and the rest genus was not highest concentration of element iron and a relatively dominant. low pH, which may result in the high percentage of

Table 6 Percentage of putative iron-oxidizing or sulfur-oxidizing bacteria in four relative samples Percentage/% Sample Acidithiobacillus Leptospirillum Sulfuricella Thiobacillus Aciditerrimonas Sulfobacillus Ferribacterium Total A 17.20 5.38 1.08 8.60 − − 1.08 33.33 D 70.83 9.72 − − 2.78 2.78 − 86.11 E 10.96 5.48 − − − − − 16.44 I 40.96 42.17 1.20 − − − − 84.34

Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342 3339

Leptospirillum. Previous studies based on metal ion not clearly classified into species, but high NH4−N and resistance showed that Leptospirillum spp. exhibited NO3−N concentrations in sample showed that this lower tolerance to Cu2+ and Co2+ [21,22], which was the organism had close relationship with denitrification and highest in sample I, but compared with other studies [9], nitrification process. that was scores of times low. The statistical product and Meiothermus demonstrated another dominance of service solutions (SPSS) based on the percentage of samples C, E, F, G and H with the percentage Leptospirillum and geochemical variables revealed that 27.40%−47.22%. This organism has the common the concentrations of Cu2+ and Fe3+ were influence characteristics described as non-sporeforming moderate factors. thermophiles with optimum growth near neutral pH and The rest five genera always occupied in sample A, capable of growth by aerobic oxidation of sugars, sugar which had the highest diversity among all samples; alcohols, and some polymers [27]. It is moderately however, the percentage of iron-oxidizing or thermophilic and is capable of starch depolymerization − − sulfur-oxidizing bacteria was low. It may be due to the and reduction of NO3 to NO2 and some Thermus strains low concentration of toxic metal ions. are known to reduce metals [28]. For samples C, E, F, G

and H, the more or less NH4−N and NO3−N may have 4.2 Communities of other predominant bacteria in close relationship with the Thermomonas and related samples Meiothermus; the rest microbial community was quite Except for the samples rich in iron-oxidizing or few. In this study, temperature was only 4−10 °C, and pH sulfur-oxidizing bacteria, there were still five samples ranged between 2.31 and 3.81, which were quite occupied with two moderate acidophilic genus including different from the former studies. It can be speculated Thermomonas and Meiothermus, and the proportion of that this environment was also suitable for Meiothermus − − them in the following samples reached 58.91%−87.50% to survive, thereby it is possible to reduce NO3 to NO2 (Table 7). Previous reports based on the bacterial and reduce metals. communities of AMD had rarely detected these two genera [23,19,10]. 4.3 Communities of abundant diversity in related samples Table 7 Percentage of other predominant bacteria in five Shannon-Weaver index H was evaluated for the relative samples phylogenetic diversity of each sample. The results Percentage/% Sample showed that sample A (H=2.36) had the preeminent Thermomonas Meiothermus Total diversity. The specific communities can be seen in C 45.07 39.44 84.51 Table 8. For sample A, the acidity was almost the same with E 31.51 27.40 58.91 samples D and I, but the community was extremely F 40.28 47.22 87.50 plentiful. Except for the composition of putative iron- G 35.29 36.76 72.06 oxidizing or sulfur-oxidizing bacteria, there still was H 43.66 39.44 83.10 more other bacteria, such as Herminiimonas, Polaromonas and Halothiobacillaceae. Herminiimonas The Thermomonas organism has an optimum was ultimately classified into (>98%) Herminiimonas growth temperature of 37−50 °C and is distantly related arsenicoxydans, which has been isolated from the to the species of the Xanthomonas [23]. For these five activated sludge of industrial plant contaminated with samples, this organism owed great advantage with the heavy metals [29]. H. arsenicoxydans was said to be able proportion of 31.51%−45.07%. However, a large amount to resist multiple toxic elements, especially arsenic by of Thermomonas sp. existed at 25°C during the oxidizing the more toxic As (III) into the less toxic cultivation of aerobic granular sludge [19]. inorganic form As (V) [30]. Polaromonas sp. strain Thermomonas fusca which was aerobic and JS666, a ß-proteobacterium, is shown so far to degrade a Gram-negative had been detected in the the nitrifying wide variety of xenobiotic compounds, including the sludge microbial community and reported in the recalcitrant groundwater contaminant cis-1, denitrification process, and also proved to have high 2-dichloroethene (cDCE). Resting cells of this strain can nitrification rate at temperature of 10 °C [24]. KIM et al also transform vinyl chloride (VC) and trichloroethene [25] discovered the existence of Thermomonas (TCE) [31]. For sample A, Cl− was predominantly rich, haemolytica in mesophilic sludge. T. haemolytica was with the concentration up to 17.86 mg/L. It can be said to grow in the temperature range of 18−50 °C and concluded that the existence of Polaromonas had close can produce acetate and propionate from carbohydrate relationship with Cl−. The appearance of fermentation [26]. For our samples, Thermomonas was Halothiobacillaceae, an obligate heterotrophs, had been

3340 Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342

Table 8 Bacterial communities of three samples with abundant diversity Clone number of Phylum Class Order Family Genus sample A Proteobacteria Betaproteobacteria Burkholderiales Oxalobacteraceae Massilia 4 Janthinobacterium 1 Herminiimonas 5 Unclassified 2 Burkholderiaceae Limnobacter 1 Comamonadaceae Albidiferax 2 Polaromonas 5 Alcaligenaceae Achromobacter 1 Unclassified 1 Rhodocyclales Rhodocyclaceae Ferribacterium 1 Unclassified 1 Hydrogenophilales Hydrogenophilaceae Thiobacillus 8 Sulfuricella 1 Unclassified 18 Gammaproteobacteria Acidithiobacillales Acidithiobacillaceae Acidithiobacillus 16 Xanthomonadales Xanthomonadaceae Lysobacter 1 Thermomonas 1 Legionellales Legionellaceae Legionella 3 Chromatiales Halothiobacillaceae 4 Unclassified 2 Alphaproteobacteria Rhizobiales Phyllobacteriaceae Phyllobacterium 1 Nitrospira Nitrospira Nitrospirales Nitrospiraceae Leptospirillum 5 Actinobacteria Actinobacteridae Actinomycetales Microbacteriaceae Leifsonia 1 Bacteroidetes Flavobacteria Flavobacteriales Flavobacteriaceae Flavobacterium 2 Sphingobacteria Sphingobacteriales Sphingobacteriaceae Pedobacter 2 Cyclobacteriaceae Algoriphagus 2 TM7 1 Unclassified 1 called moderate acidophiles [18], and was previously strength [9], including some mesophilic iron considered to grow by sulfur oxidation only, which was (II)-oxidizing archaea, such as F. thermophilum, latterly isolated from AMD as iron-oxidizing bacteria in Ferroplasma acidiphilium and Ferroplasma moderately acidic (~pH 4) solid media [1]. acidarmanus [9]. It was reported that F. thermophilum was often flourishing at extremely low pH (lower than 4.4 Archaeal communities’ diversity 1.4), high concentration of total iron, ferrous iron and Archaea were detected in all eight samples; and other heavy metals [1]. According to ZHANG et al [32], they were classified into three known genus: during the bioleaching of chalcopyrite, F. thermophilum Ferroplasma, Thermoplasma, Thermogymnomonas and L1 was capable of chemomixotrophic growth on ferrous agenus unclassified, all of which belong to iron and organic matters; moreover, it could relieve Thermoplasmatales order. According to previous toxicity of organic matters to autotrophic bacteria. F. research, all the archaea in this order are heterotrophic acidiphilumis, described as a strictly except Ferroplasma, which has the ability to gain energy chemolithoautotrophic microbe, can oxidize Fe2+ from during the oxido−reduction of iron. All the archaea in Fe2SO4 and pyrite FeS2. It is the only described archaeon Thermoplasmatales order tend to be thermophilic, capable of growth at the relatively low temperatures especially for Thermoplasma and Thermogymnomonas, commonly encountered in AMD. Compared with F. while with the exception of Ferroplasma. thermophilum, the use of organic compounds as carbon The genus of Ferroplasma is dominant in the most sources has not been reported thus far [33]. The extreme environment of lower pH and higher ionic Ferroplasma genus detected in our samples was not

Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342 3341 classified into species, but it was important for the mineral spoils and drainage waters at abandoned coal and metal iron-/sulfur- oxidation. mines [J]. Water, Air Soil Pollution Focus, 2003, 3: 47−66. Archaea in Thermoplasma and Thermogymnomonas [3] HALLBERG K B. New perspectives in acid mine drainage microbiology [J]. Hydrometallurgy, 2010, 104: 448−453. were detected in extremely thermoacidophilic [4] PESIC B, OLIVER D J, WICHLACZ P. An electrochemical method environment, such as burning coal refuse pile in USA of measuring the oxidation rate of ferrous to ferric iron with oxygen and volcanic solfataric field in Italy, with the growth in the presence of Thiobacillus ferrooxidans [J]. Biotechnology and temperature of 33−67 °C, pH 0.5−4 [34]. The detection Bioengineering, 1989, 33(4): 428−439. of them in the eight samples showed that the acidic water [5] GUO Yao-guang, HUANG Peng, ZHANG Wu-gang, YUAN Xue-wu, FAN Feng-xia, WANG Huan-li, LIU Jian-she, WANG Zhao-hui. was not “cold” based on the archaeal communities and Leaching of heavy metals from Dexing copper mine tailings pond [J]. the growth temperature for Thermoplasma and Transactions of Nonferrous Metals Society of China, 2013, 23(10): Thermogymnomonas was not limited. The existence of 3068−3075. heterotrophic archaea in Thermoplasma and [6] HAO Chun-bo, WANG Li-hua, GAO Ya-nan, ZHANG Li-na, DONG Thermogymnomonas may create a more suitable Hai-liang. Microbial diversity in acid mine drainage of Xiang environment for the growth of the iron-oxidizers by mountain sulfide mine, Anhui Province, China [J]. Extremophiles, 2010, 14: 465−474. removing organic compounds that can be toxic to the [7] YUAN Xue-wu, XIE Xue-hui, FAN Feng-xia, ZHU Weng-xiang, autotroph [3]. Samples E and F were abundant in LIU Na, LIU Jian-she. Effects of mutation on a new strain Thermoplasma and Thermogymnomonas, with the Leptospirillum ferriphilum YXW and bioleaching of gold ore [J]. percentages of 68.75% and 70.96%, respectively. It may Transactions of Nonferrous Metals Society of China, 2013, 23(9): have close relationship with the organic carbon, for the 2751−2758. [8] PIETRO M, CRISTINA C, PAOLA C, FRANCESCO F, COD of these two samples being relatively high, GABRIELLA L. Mineralogical and chemical evolution of ochreous reaching 156.3 mg/L and 143.8 mg/L accordingly. precipitates from the Libiola Fe−Cu-sulfide mine (Eastern Liguria, Italy) [J]. Applied Geochemistry, 2012, 27(3): 577−589. 5 Conclusions [9] HE Zhi-guo, XIAO Sheng-mu, XIE Xue-hui, HU Yue-hua. Microbial diversity in acid mineral bioleaching systems of Dongxiang copper 1) The UPGMA cluster analysis based on the mine and Yinshan lead−zinc mine [J]. Extremophiles, 2008, 12: 225−234. microbial communities’ compositions revealed that these [10] XIAO Sheng-mu, XIE Xue-hui, LIU Jian-she. Microbial eight samples were divided into three parts, including the communities in acid water environments of two mines, China [J]. samples rich in iron-/sulfur-oxidizing microorganisms; Environmental Pollution, 2009, 157: 1045−1050. samples rich in moderate acidophiles (Meiothermus, [11] SUN Qing-ye, AN Shu-qing, YANG Lin-zhang, WANG Thermomonas); and sample without dominant species Zhong-sheng. Chemical properties of the upper tailings beneath biotic crusts [J]. Ecological Engineering, 2004, 23(1): 47−53. but with abundant diversity. [12] XU De-cong, ZHAN Jing, CHEN Zheng, GAO Yi, XIE Xian-zheng, 2) The acidophilic microorganism existing in the SUN Qing-ye, DOU Chang-ming. Effects of Vetiveria zizanioides L. mine drainage had close relationship with the growth on chemical and biological properties of copper mine tailing surrounding environment, The dominance of wastelands [J]. Acta Ecologica Sinica, 2012, 32 (18): 5683−5691. Acidithiobacillus spp. had close relationship with the [13] ZHAN Jing, SUN Qin-ye. Diversity of free-living nitrogen-fixing concentration of Fe3+, NO −, SO 2− and EC value, microorganisms in wastelands of copper mine tailings during the 3 4 process of natural ecological restoration [J]. Journal of Leptospirillum spp. was significantly associated with the Environmental Sciences, 2011, 23: 476−487. 2+ 3+ concentrations of Cu and Fe . [14] HUMAYOUN S B, BANO N, HOLLIBAUGH J T. Depth 3) Except for A. ferrooxidans, A. thiooxidans, and L. distribution of microbial diversity in Mona lake, a mermictic soda ferrooxidans dominanting in AMD, there still was some lake in California [J]. Applied and Environmental Microbiology, thermophilic microorganism, such as Meiothermus, 2003, 69: 1030−1042. [15] QIU Guan-zhou, WAN Min-xi, QIAN Lin, HUANG Zhi-ying, LIU Thermomonas and Thermoplasmatales at the low pH, Kai, LIU Xue-duan, SHI Wu-yang, YANG Yu. Archaeal diversity in while the influence factor causing the abundance of acid mine drainage from Dabaoshan mine, China [J]. Journal of Meiothermus and Thermomonas was not clear. It might Basic Microbiology, 2008, 48: 401−409. be affected synthetically by pH, ion concentration, [16] ZHOU Zhi-jun, YIN Hua-qun, LIU Yi, XIE Ming, QIU Guan-zhou, LIU Xue-duan. Diversity of microbial community at acid mine especially by high NH4−N and NO3−N concentrations. drainages from Dachang metals-rich mine, China [J]. Transactions of Nonferrous Metals Society of China, 2010, 20(6): 1097−1103. References [17] XIE Jian-ping, JIANG Hong-chen, LIU Xin-xing, LIU Xue-rui, ZHOU Ji-zhong, QIU Guan-zhou. 16s rDNA based microbial [1] SCHIPPERS A, BREUKER A, BLAZEJAK A, BOSECKER K, diversity analysis of eleven acid mine drainages obtained from three KOCK D, WRIGHT T L. The biogeochemistry and microbiology of Chinese copper mines [J]. Journal of Central South University of sulfidic mine waste and bioleaching dumps and heaps, and novel Fe Technology, 2011, 18: 1930−1939. (II)-oxidizing bacteria [J]. Hydrometallurgy, 2010, 104(3−4): [18] MURAVYOV M I, BULAEV A G. Two-step oxidation of a refractory 342−350. gold-bearing sulfidic concentrate and the effect of organic nutrients [2] JOHNSON D B. Chemical and microbiological characteristics of on its biooxidation [J]. Minerals Engineering, 2013, 45: 108−114.

3342 Yang YANG, et al/Trans. Nonferrous Met. Soc. China 24(2014) 3332−3342 [19] SONG Zhi-wei, REN Nan-qi, ZHANG Kun, TONG Long-yan. Geobiology, 2011, 9: 471−480. Influence of temperature on the characteristics of aerobic granulation [28] ERROL D C, LIZELLE A P, ESTAVAN H. Reduction of U(VI) by in sequencing batch airlift reactors [J]. Journal of Environmental the deep subsurface bacterium, Thermus scotoductus SA-01, and the Sciences, 2009, 21: 273−278. involvement of the ABC transporter protein [J]. Chemosphere, 2012, [20] CHENG Yi, GUO Zhao-hui, LIU Xue-duan, YIN Hua-qun, QIU 86(6): 572−577. Guan-zhou, LIU Hong-wei. The bioleaching feasibility for Pb/Zn [29] MULLER D, SIMEONOVA D D, RIEGEL P, MANGENOT smelting slag and community characteristics of indigenous moderate- S, KOECHLER S, LIEVREMONT D, BERTIN P N, LETT M C. thermophilic bacteria [J]. Bioresource Technology, 2009, 100: Herminiimonas arsenicoxydans sp. nov., a metalloresistant bacterium 2737−2740. [J]. International Journal of Systematic and Evolutionary [21] HE Zhi-guo, YIN Zhen, WANG Xin, ZHONG Hui, SUN Wei. Microbiology, 2006, 56: 1765−1769. Microbial community changes during the process of pyrite [30] WEISS S, CARAPITO C, CLEISS J, KOECHLER S, TURLIN E, bioleaching [J]. Hydrometallurgy, 2012, 125−126: 81−89. COPPEE J Y, HEYMANN M, KUGLER V, STAUFFERT M, [22] LIN Hai, ZHU Yi-jun, DONG Ying-bo, CHENG Huang, HUO CRUVEILLER S, MEDIGUE C, VAN-DORSSELAER A, BERTIN Han-xin. Breeding and adsorption properties investigation of a strain P N, ARSENE-PLOETZE F. Enhanced structural and functional resistant to acid and copper ions [J]. Environmental Chemistry, 2013, genome elucidation of the arsenite-oxidizing strain Herminiimonas 32(4): 599−604. arsenicoxydans by proteomics data [J]. Biochimie, 2009, 91: [23] MARTA P A, FRED A R, FERNANDA M N, MILTON S C. 192−203. Thermomonas hydrothermalis sp. nov.: A new slightly thermophilic [31] ADEMOLA O O, ADHIKA B, BALAKRISHNA P. Quantitative γ-Proteobacterium isolated from a hot spring in central portugal [J]. assessment of the toxic effects of heavy metals on 1, Systematic and Applied Microbiology, 2003, 26: 70−75. 2-dichloroethane biodegradation in co-contaminated soil under [24] THOMAS F D, MATIAS B V, ANTHONY D S, ARIEL A S, APREL aerobic condition [J]. Chemosphere, 2011, 85(5): 839−847. Q E. Characterization of a microbial community capable of [32] ZHANG Li-juan, JI Hou-guo, WANG Yu-guang, WAN Li-li, ZHOU nitrification at cold temperature [J]. Bioresource Technology, 2010, Hong-bo. Synergies between archaea Ferroplasma thermophilum and 101: 491−500. two moderately thermophilic bacteria under stress of yeast extract or [25] KIM W, HWANG K, SHIN S G, LEE S, HWANG S. Effect of high Cu2+ [J]. The Chinese Journal of Nonferrous Metals, 2013, 23(1): temperature on bacterial community dynamics in anaerobic 265−273. (in Chinese) acidogenesis using mesophilic sludge inoculum [J]. Bioresource [33] MOHSEN F, TSUYOSHI H. Hydrophilicity of Ferroplasma Technology, 2010, 101: S17−S22. acidiphilum and its effect on the depression of pyrite [J]. Minerals [26] WOONG K, KWANGHYUN H, SEUNG G S, SEUNGYON G, Engineering, 2012, 36−38: 242−247. SEOKHWAN H. Effect of high temperature on bacterial community [34] PLUMB J J, HADDAD C M, GIBSON J A, FRANZMANN P D. dynamics in anaerobic acidogenesis using mesophilic sludge Acidianus sulfidivorans sp. nov., an extremely acidophilic, inoculum [J]. Bioresource Technology, 2010, 101(1): S17−S22. thermophilic archaeon isolated from a solfatara on Lihir Island, [27] HEDLUND B P, MCDONALD A I, LAM J, DODSWORTH J A, Papua New Guinea, and emendation of the genus description [J]. BROWN J R, HUNGATE B A. Potential role of Thermus International Journal of Systematic and Evolutionary Microbiology,

thermophilus and T. oshimai in high rates of nitrous oxide (N2O) 2007, 57: 1418−1423. production in 80 °C hot springs in the U.S. Great Basin [J].

铜陵重金属富集的尾矿废弃地酸性废水中细菌及古菌的多样性

杨扬，李杨，孙庆业

安徽大学资源与环境工程学院，合肥 230601

摘要：为了加深对安徽省铜陵市不同重金属富集程度的尾矿附近酸性废水中微生物多样性的了解，运用 PCR-16S rDNA 克隆文库技术对酸性废水中细菌及古菌的群落结构进行研究。在铜陵的 5 个样点采集了 8 个水样。系统发育分析结果表明，酸性废水中的细菌主要是 Betaproteobacteria, Gammaproteobacteria, Alphaproteobacteria, Deinococcus-Thermus, Nitrospira, Firmicutes, Actinobacteria, Deltaproteobacteria, Bacteroidetes, Chloroflexi，古菌是 Thermoplasma, Ferroplasma 以及 Thermogymnomonas。根据细菌和古菌的组成对样品进行聚类分析，结果表明， 5 个样品由于优势菌株 Thermomonas 和 Meiothermus 拥有较高的相似度。2 个样品由于 Acidithiobacillus 和 Leptospirillum 占主导也拥有较高的相似度。剩余的样品多样性较高，拥有最高的香浓-微纳指数 2.91。典型相关 2+ 2+ − 2− 分析 CCA 的结果表明微生物的多样性组成与理化因子有密切的关系，如水的 pH 以及 Hg 、Pb 、Cl 、SO4 、 Fe3+的含量。关键词：酸性矿业废水；微生物结构组成；克隆文库；理化因子 (Edited by Xinag-qun LI)